1. Field of the Invention
Implementations described herein relate generally to information searching and, more particularly, to ranking search results using a global ranking algorithm modified by user preferences.
2. Description of Related Art
Existing information searching systems use search queries to search through aggregated data to retrieve specific information that corresponds to the received search queries. Such information searching systems may search information based locally or in distributed locations. The World Wide Web (“web”) is one example of information in distributed locations. The web contains a vast amount of information, but locating a desired portion of that information can be challenging. This problem is compounded because the amount of information on the web, and the number of new users inexperienced at web searching, are growing rapidly.
Search engines attempt to return hyperlinks to web documents in which a user is interested. Generally, search engines base their determination of the user's interest on search terms (e.g., in a search query provided by the user). The goal of the search engine is to provide links to high quality, relevant results to the user based on the search query. Typically, the search engine accomplishes this by matching the terms in the search query to a corpus of pre-stored web documents. Web documents that contain the user's search terms are considered “hits” and are returned to the user.
Search results provided to a user in response to a search query are typically ranked in some fashion to present the more useful, or relevant, documents higher in the list of search results, and to present the less useful, or relevant, documents lower in the list of search results. To rank the results of a search, a global document ranking algorithm, such as, for example, a link-based ranking algorithm, is sometimes used. Link-based ranking may approximate a most-inclusive community estimation of the quality of a document. However, on any given topic there may be sub-communities that would assign greatly different rankings to documents as compared to a global link-based ranking approach. Often, a user would prefer to see results returned in an order that corresponds to the ranking of the sub-community with which his opinions are most congruent. For example, in a query regarding nutrition, one user might want to see results cited by government agencies, while another might prefer results cited by bodybuilding authorities. Existing global document ranking algorithms, thus, do not resolve personal differences in search result ranking